1. Field
The following description relates to a technology of evaluating quality of automatic translation using a distributed representation.
2. Description of Related Art
Quality of machine translation translated by an automatic translator may be evaluated using a manual evaluation method or an automatic evaluation method. An expert who is familiar with both a source language and a target language is needed to manually evaluate an automatic translation. For example, an expert grades an automatically translated result based on two criteria, fluency and adequacy. Fluency represents whether a translation contains natural sentences, and adequacy represents whether the meaning of an original text is expressed effectively in the translated language. The automatic evaluation method includes manually generating a reference translation of an original text and evaluating similarity between an automatically translated result and the manually generated reference translation.
Bilingual evaluation understudy (BLEU) is widely used as the automatic evaluation method. BLEU evaluates how many times adjacent n-words which exist in the automatically translated result (n-gram) appear in the manually generated translation. Although the conventional automatic evaluation method has an advantage over the manual evaluation method, since it only considers a case in which the automatically translated result and the manually translated result accurately correspond to each other, a case in which an excellent translation result is graded low or an incorrect translation is graded high occurs.